Installation Reference

This page details system requirements, advanced installation options and troubleshooting steps.

System Requirements

Celldetective is versatile and can run on standard workstations or high-performance clusters.

CPU: Modern multi-core processor (Intel Core i7/i9 or equivalent).
RAM:
- Minimum: Sufficient to load a single movie stack into memory (dependent on image size).
- Recommended: 16 GB+ for smooth visualization in Napari.
GPU (Optional but Recommended):
- NVIDIA GPU with CUDA support (e.g., RTX 3070, 8GB VRAM).
- Greatly accelerates Deep Learning inference (StarDist, Cellpose).
- Note: CPU-only mode is fully supported but slower.

OS:
- Windows 10/11
- Linux (Ubuntu 20.04 LTS recommended)
- MacOS (Experimental, TensorFlow setup varies)
Python: Version 3.9 to 3.11.
Dependencies: managed via pip/conda (see Get started).

We recommend using conda to create a clean environment for Celldetective.

Create an environment (Python 3.9 - 3.11):

$ conda create -n celldetective python=3.11 pyqt
$ conda activate celldetective

To run the latest development version:

Clone the repository:

$ git clone git://github.com/celldetective/celldetective.git
$ cd celldetective

Create and activate environment:

$ conda create -n celldetective python=3.11 pyqt
$ conda activate celldetective

Install in editable mode:

$ pip install -r requirements.txt
$ pip install -e .

$ pip install git+https//github.com/celldetective/celldetective.git

Microsoft Visual C++ (Windows)

The installation of mahotas on Windows requires Microsoft Visual C++ 14.0 or greater. Download it from the Visual Studio Build Tools.

NVIDIA GPU Support

To use your NVIDIA GPU, ensure you have installed: * Proper NVIDIA Drivers * CUDA Toolkit * cuDNN libraries

We recommend installing TensorFlow with CUDA support via conda or pip (e.g., pip install tensorflow[and-cuda]).